code: def _center_to_corners_format_numpy(
      bboxes_center: np.ndarray,
  ) -> np.ndarray:
      center_x, center_y, width, height = bboxes_center.T
      bboxes_corners = np.stack(
          # top left x, top left y, bottom right x, bottom right y
          [
              center_x - 0.5 * width,
              center_y - 0.5 * height,
              center_x + 0.5 * width,
              center_y + 0.5 * height,
          ],
          axis=-1,
      )
      return bboxes_corners
  
imports: import warnings
  from typing import Iterable, List, Optional, Tuple, Union
  import numpy
  from .image_utils import ChannelDimension, ImageInput, get_channel_dimension_axis, get_image_size, infer_channel_dimension_format
  from .utils import ExplicitEnum, TensorType, is_jax_tensor, is_tf_tensor, is_torch_tensor
  from .utils.import_utils import is_flax_available, is_tf_available, is_torch_available, is_vision_available, requires_backends
label_desc: Use image node_id 10 for calling a global function with example usage: _center_to_corners_format_numpy(bboxes_center) and returns: bboxes_corners